Mercury is among the most chemically complex and environmentally hazardous elements encountered in legacy nuclear waste and industrial streams. It can exist in multiple oxidation states, primarily Hg(I) (mercurous) and Hg(II) (mercuric), and forms a wide array of inorganic salts and organometallic complexes. Understanding how these species behave under different chemical conditions is vital for waste treatment, remediation, and long-term storage strategies (Blanc et al., 2018).
Mercury’s behavior is particularly challenging to predict due to its tendency to partition between phases, form both stable and metastable solids, and complex with a wide range of chemical species (Schuster, 1991). Its environmental persistence and strong bioaccumulation potential have made it a high priority for regulatory agencies, leading to strict limits on emissions and disposal. In both aqueous and vapor forms, mercury is present in critical systems such as gas scrubbers and waste tanks – making accurate modeling essential for ensuring safety and regulatory compliance (Rogers & McDuffie, 1991).
At OLI, we have extended our Mixed-Solvent Electrolyte (MSE) model with a comprehensive update to support mercury chemistry in the context of nuclear waste management. This addition enables predictive modeling of thermodynamic properties, solubility equilibria, and the speciation of a wide range of mercury compounds. By utilizing the MSE framework, we provide an accurate and consistent approach for understanding how mercury behaves across diverse process conditions – from acidic leachates to gas scrubbing systems and high-ionic-strength waste brines.
This addition to the OLI MSE databank represents a significant advancement in the thermodynamic modeling of mercury chemistry. This expansion integrates a diverse set of mercurous and mercuric species, selected for their relevance to environmental remediation, and nuclear waste management. The compounds incorporated include:
- Mercurous species (Hg+): formate, glycolate, and oxalate
- Mercuric species (Hg2+): nitrate, formate, glycolate, and oxalate
- Organomercury species: dimethylmercury, methylmercury chloride, methylmercury hydroxide, and methylmercury nitrate
Among the species incorporated, three systems stand out for their complexity, modeling challenges, and environmental significance: mercuric nitrate, dimethylmercury, and methylmercury nitrate. These compounds span a wide range of chemical behaviors from low-solubility solids to highly volatile organometallics.
Mercuric Nitrate (Hg(NO3)2):
Mercuric nitrate plays a key role in acidic waste environments and has multiple solid-phase forms depending on nitric acid concentration and temperature. Using data from solubility measurements, the MSE model accurately reproduced the phase boundaries between HgO, Hg(NO3)2.2HgO, and Hg(NO3)2.H2O. These predictions inform solubility limits, precipitate formation, and solid-phase transitions under varying HNO3 concentration. As shown in Figure 1, the model prediction is in good agreement with experimental data from Cox (1904), capturing both solubility trends and the solid phase transition. HgO is stable at relatively low HNO3 concentration followed by Hg(NO3)2·2HgO. Both solids coexist at the concentration of nitric acid and mercury nitrate marked with a green symbol. As the acidity of the system increases, a shift in solid-phase stability occurs. Mercury nitrate monohydrate starts to precipitate at HNO3 concentration above 1 m at 25oC, which is marked with a light blue symbol. This modeling capability is crucial for predicting and managing mercury contamination in complex high-acid waste systems.
Figure 1. A comparison between experimental data and the MSE predictions of the solubility of Hg(NO3)2 in HNO3 at 25 oC.
Dimethylmercury ((CH3)2Hg):
Dimethylmercury, known for its extreme toxicity and volatility, is a challenging compound to simulate due to its tendency to partition between aqueous and gas phases and, under certain conditions, form a distinct organic liquid phase. By incorporating vapor pressure and solubility data, along with Henry’s constant, the MSE model successfully constructed the phase diagram of the (CH3)2Hg–H2O system at 25 oC, capturing the VLE, LLE, and VLLE regions (see Figure 2). The ability to model VLLE behavior provides valuable insight into the conditions under which phase separation may occur. Such predictive modeling is essential for designing safer processing and storage strategies for volatile mercury species.
Figure 2. MSE prediction of the (CH3)2Hg–H2O phase diagram at 25oC, along with the experimental LLE data points.
Methylmercury Nitrate (CH3HgNO3):
According to our literature review, the only experimental data available for methylmercury nitrate (CH3HgNO3) are its melting point values, reported by Johns et al. (1930) and Bach et al. (1986). In the absence of direct solubility data, we employed a family similarity analysis, an estimation technique that leverages trends across chemically related compounds. Given the structural similarity between CH3HgNO3 and methylmercury chloride (CH3HgCl), it was assumed that both species would exhibit comparable solubility behavior, with CH3HgNO3 expected to be more soluble due to its significantly lower melting point (59–60oC vs. 171oC). The MSE model was regressed using extensive experimental solubility data for CH3HgCl and then extended to CH3HgNO3. As shown in Figure 3, the predicted solubility curve for CH3HgNO3 aligns with expectations and highlights the model’s ability to produce thermodynamically consistent behavior for compounds lacking experimental data; notably, the predicted melting point of 59.225°C closely matches the reported experimental values of 59°C and 60°C.
Figure 3. MSE solubility prediction of CH3HgNO3 relative to CH3HgCl, along with a comparison between the predicted and experimental melting points.
This addition to the OLI MSE databank significantly enhances our ability to model mercury, enabling its application across a wide range of waste treatment and environmental management scenarios. As environmental regulations tighten and legacy waste sites continue to age, robust modeling tools like the OLI MSE framework will be critical for supporting safer, more effective, and sustainable decision-making across the nuclear, industrial, energy, and environmental sectors.
The new mercury compounds will be available in the next release of OLI software. For more information or to speak with our experts, please don’t hesitate to contact us.
References
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